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import math

def poissoniana(x, mu):
    return (numpy.exp(-mu) * mu**x)/ (scipy.misc.factorial(x)) # if x >= 0

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x = numpy.linspace(1,1000,1000)
# y = poissoniana(x, 3)
y = dataframeGradi.Tre.values

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popt, pcov = scipy.optimize.curve_fit(poissoniana, x, y)

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y, x = numpy.histogram(dataframeGradi.aggregati.values, bins = 3)

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min(dataframeGradi.aggregati.values)

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len(y),len(x)

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y,x

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arr = [5,5,5,5,5,6,6,6,7,7]

y, x = numpy.histogram(numpy.array(arr), bins=(5,6,7,8))

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y,x

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pyplot.hist(arr, bins=(5,6,7,8))

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pyplot.hist(arr, bins=3)

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pyplot.hist(arr, bins=3, align="left")

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pyplot.hist(arr, bins=(5,6,7,8), align="mid")

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pyplot.hist(arr, bins=(5,6,7,8), align="left")

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def integerHistogram(integerData):
    integerData = [5,5,5,5,5,6,6,6,7,7]
    minimum = min(integerData)
    maximum = max(integerData)
    integerBins = maximum - minimum + 1
    numberSet = numpy.linspace(minimum, maximum, integerBins)
    y, x = numpy.histogram(arr, bins=(5,6,7,8))

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numpy.histogram(arr, bins=(5,6,7,8))

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integerData = [5,5,5,5,5,6,6,6,7,7,9,10,10]
minimum = min(integerData)
maximum = max(integerData)
integerBins = maximum - minimum + 1
numberSet = numpy.linspace(minimum, maximum, integerBins, dtype=int)
min(integerData), max(integerData)

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numberSet

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numpyBins = numberSet + [minimum+1]

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numpyBins

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